System Identification and Optimal Control Engineer

Burlington, Massachusetts, United States | Full-time

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If you have a desire to grow with a dynamic company making a major contribution to renewable energy, have great advancement opportunities as we expand our solutions worldwide, and thrive in a fast paced, exciting environment, then this opportunity with WindESCo is for you.

WindESCo is a rapidly growing company helping to create a better planet by increasing the green energy output from existing wind farms. We do this by combining the power of engineering, machine learning and IIoT. Our solutions are currently optimizing wind plants in 8 countries across 3 continents. We have an immediate opening in our R&D team for an engineer to work on developing technology for wind plan optimization at our headquarters in Burlington, MA. Initially new employees will work primarily remotely due to Covid-19 until it is safe to return to the office. We are looking for candidates that think big, can thrive in our team-oriented culture and want to help change the world with our solutions.

Permanent US work authorization is required (US citizen, green card, or equivalent). Applicants with, F1, OPT, H1B or similar current visa status requiring sponsorship will not be considered.

To learn more about WindESCo, please visit windesco.com or view our corporate video. Please apply here.

System Identification and Optimal Control Engineer

To support our growth, we are looking for an engineer to work on system identification and control optimization problems. In this role you will apply machine learning and AI techniques to create solutions that enhance our products for maximizing the energy production of existing wind plants by enabling wind turbines to work together more efficiently. This work will include modeling existing linear and non-linear system behavior of turbines using observed data and developing optimized controllers for modifying the behavior of these systems by generating modified or synthetic inputs. This role will extend from developing specific algorithms to developing software for distributed systems that can improve over time and working on advanced algorithms for wind plant optimization.

You will need to be an innovative thinker who is able to apply principles of control theory and data science to large time series datasets and develop practical robust algorithms. You are excited about understanding and designing control systems, conducting experiments, developing test cases, and writing good quality code. The position requires attention to detail in addition, experimental data analysis and applied problem solving abilities. A validation-driven development mindset is key—always looking for possible ways things break. You will need to be well organized, be able to innovate under deadlines and collaborate effectively with others.

At WindESCo you will be expected to innovate, demonstrate superiority of potential innovations through rigorous testing and validation, and execute by turning innovative concepts into production systems. WindESCo is a young and growing company, so you will need to wear many hats, and there are many opportunities to grow with the company.

Job Responsibilities

●  Perform system identification analysis and “black-box” machine learning modeling of nonlinear control systems using time-series data.
●  Develop algorithms to maximize performance of control loops for nonlinear systems, leveraging machine learning algorithms as appropriate.
●  Research and apply algorithms for automated control system optimization.
●  Create data visualizations and analysis tools.

●  Write production quality code with high standards for quality, maintainability, and automated testing.

●  Use Git version control to effectively collaborate with other team members.

 

 

Requirements

●  You are an innovative thinker who loves applied problem solving in a fast-paced environment.
●  You are also passionate about code quality and testing.

●  Master’s degree in STEM and 2+ years relevant experience or a Ph.D. in STEM and a relevant dissertation topic or experience.

●  Expertise in control system design optimization and practical application to physical systems.
●  Experience applying machine learning techniques.
●  Basic understanding of newtonian physics, mechanics, electrical energy, aerodynamics.
●  Strong technical communication and organization skills.

●  Eligible to work in the US.

 

Preferred Qualifications (The ideal candidate will have one or more of the following):

●  Demonstrated programming skills in Python using Pandas, SciPy and scikit-learn.
●  Wind turbine SCADA data analysis experience.
●  Experience with analog and digital signal processing.
●  Knowledge of wind turbine and wind plant control systems.
●  Experience with wind turbine and wind plant simulation software (FAST, FLORIS, SOWFA, etc.)
●  Hands-on experience implementing control algorithms on physical systems.
 
Benefits
WindESCo provides competitive compensation plans. In addition, you would receive excellent health and dental insurance, 401k, and paid time off.
 
WindESCo has established a progressive workplace that is collaborative, and team focused. If you believe you would be an excellent fit and would like to join the WindESCo team, please submit your resume at https://windesco.recruiterbox.com/